A Multiplicative Seasonal ARIMA/GARCH Model in EVN Traffic Prediction

Quang Thanh Tran¹, Zhihua Ma², Hengchao Li¹, Li Hao¹, Quang Khai Trinh³

¹Sichuan Provincial Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China.
²Beijing Branch of China United Network Communications Co. Ltd., Beijing, China.
³Telecommunication Department, University of Transport and Communications, Hanoi, Vietnam.

DOI: 10.4236/ijcns.2015.84005                

Abstract

This paper highlights the statistical procedure used in developing models that have the ability of capturing and forecasting the traffic of mobile communication network operating in Vietnam. To build such models, we follow Box-Jenkins method to construct a multiplicative seasonal ARIMA model to represent the mean component using the past values of traffic, then incorporate a GARCH model to represent its volatility. The traffic is collected from EVN Telecom mobile communication network. Diagnostic tests and examination of forecast accuracy measures indicate that the multiplicative seasonal ARIMA/GARCH model, i.e. ARIMA (1, 0, 1) × (0, 1, 1)24/GARCH (1, 1) shows a good estimation when dealing with volatility clustering in the data series. This model can be considered to be a flexible model to capture well the characteristics of EVN traffic series and give reasonable forecasting results. Moreover, in such situations that the volatility is not necessary to be taken into account, i.e. short-term prediction, the multiplicative seasonal ARIMA/GARCH model still acts well with the GARCH parameters adjusted to GARCH (0, 0).

Keywords

Traffic Prediction, ARIMA, GARCH, Multiplicative Seasonal ARIMA/GARCH, EViews

Conflicts of Interest

The authors declare no conflicts of interest.

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